Mr. DLib's Recommendations as a Service (RaaS) allows operators of academic products to easily integrate a scientific recommender system into their products. The basic idea of Mr. DLib's scientific recommender system is to calculate recommendations for research articles, call for papers, grants, etc. on Mr. DLib's server. Operators of academic products may then request recommendations from Mr. DLib and display the recommendations to their users. The effort for such an integration is a few hours or days for the operator, compared to several months when developing one’s own recommender system. Currently, Mr. DLib's recommender system is used by the pilot partner GESIS and soon by the reference manager JabRef. Mr. DLib is open source and its goal is to facilitate the application of and research on scientific recommender systems.
- helps academic service providers enhance their own portfolio, e.g., by providing more precise literature recommendations
- supports researchers in need for (large amounts of) bibliographic data or scholarly full-texts, e.g., to perform impact or trend analyses
- provides a base to other agents for building own services upon the data of Mr. DLib.
[2017a] Mr. DLib: Recommendations-as-a-Service (RaaS) for Academia
Beel, Joeran, Bela Gipp, and Akiko Aizawa
In Proceedings of the ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), 2017
[2017b] RARD: The Related-Article Recommendation Dataset
Beel, Joeran, Zeljko Carevic, Johann Schaible, and Gabor Neusch
D-Lib Magazine 23, no. 7/8 (July 2017): 1–14